Introduction to data science

11. Which of the following is NOT a key role in a typical Data Science team?

Data Engineer
Data Analyst
Data Scientist
Database Administrator

Detailed SolutionWhich of the following is NOT a key role in a typical Data Science team?

12. Which of the following principle is incorrectly represented in the below figure?

Show Comparisons
Integrate Evidence
Describe Evidence
None of the mentioned

Detailed SolutionWhich of the following principle is incorrectly represented in the below figure?

13. What is the primary objective of data exploration in Data Science?

To build predictive models
To find hidden patterns
To summarize data
To collect data

Detailed SolutionWhat is the primary objective of data exploration in Data Science?

14. In Data Science, what is the purpose of feature engineering?

To extract features from data
To visualize data features
To clean data features
To model data features

Detailed SolutionIn Data Science, what is the purpose of feature engineering?

15. Point out the correct statement.

Machine learning focuses on prediction, based on known properties learned from the training data
Data Cleaning focuses on prediction, based on known properties learned from the training data
Representing data in a form which both mere mortals can understand and get valuable insights is as much a science as much as it is art
None of the mentioned

Detailed SolutionPoint out the correct statement.

16. Which of the following command line environment is used for interacting with Git?

GitHub
Git Bash
Git Boot
All of the mentioned

Detailed SolutionWhich of the following command line environment is used for interacting with Git?

17. Which of the following is NOT typically considered a part of the Data Science process?

Data Collection
Data Visualization
Data Cleaning
Software Development

Detailed SolutionWhich of the following is NOT typically considered a part of the Data Science process?

18. Raw data should be processed only one time.

TRUE
nan
nan
nan

Detailed SolutionRaw data should be processed only one time.

19. What is the process of converting categorical variables into numerical values for machine learning called?

Feature Extraction
Data Encoding
Data Standardization
Label Encoding

Detailed SolutionWhat is the process of converting categorical variables into numerical values for machine learning called?

20. Which of the following would be more appropriate to be replaced with question mark in the following figure?

Data Analysis
Data Science
Descriptive Analytics
None of the mentioned

Detailed SolutionWhich of the following would be more appropriate to be replaced with question mark in the following figure?

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